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A Machine Learning Prediction Model for Postoperative Acute Kidney Injury in Non-Cardiac Surgery Patients

RECRUITINGSponsored by Lanyue Zhu
Actively Recruiting
SponsorLanyue Zhu
Started2025-07-01
Est. completion2026-12-31
Eligibility
Age18 Years+
Healthy vol.Accepted
View on ClinicalTrials.gov →

NCT07030166

Summary

Primary objectives of this study is to develop and validate a predictive model for acute kidney injury after non-cardiac surgery based on machine learning. Secondary objectives of this study is to incorporate frailty assessment as a new predictor into the model and measure its incremental value was measured.

Eligibility

Age: 18 Years+Healthy volunteers accepted
Inclusion Criteria:

* 18 years old or above
* Undergo non-cardiac surgery

Exclusion Criteria:

* At least one measurement of serum creatinine (SCr) was not conducted before and after the operation
* End-stage renal disease (ESRD) that has received dialysis within the past year
* Baseline SCr ≥ 4.5 mg/dl (because the clinical criteria for AKI based on elevated SCr may not be applicable to these patients)
* Acute kidney injury occurred within 7 days before the operation
* The operation time is less than 2 hours

Conditions2

Heart DiseaseKidney Injury, Acute

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